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动力吸振器被广泛用于船舶、飞机和汽车等工业领域。在结构振动控制中,为了最大限度地发挥吸振器的耗能减振作用,需要寻找吸振器的最优参数,即最优频率比、最优阻尼比和最优质量比,使得结构在不同的频率激励下获得最好的减振效果。文章将基于进化算法的多目标优化技术与多属性决策方法联合运用,针对主系统存在阻尼的减振系统,研究了动力吸振器的优化和决策问题。对于多目标优化问题,采用改进的非支配解排序的多目标进化算法(NSGAII),求出Pareto最优解,由这些Pareto最优解构成决策矩阵,使用客观赋权的信息熵方法对最优解的属性进行权值计算,然后用逼近理想解的排序方法(TOPSIS)进行多属性决策(MADM)研究,对Pareto最优解给出排序。文中给出了4个设计参数、3个目标函数的动力吸振器优化设计算例。
Dynamic vibration absorbers are widely used in ships, aircraft and automotive industries. In the structural vibration control, in order to maximize the energy dissipation effect of the vibration absorber, it is necessary to find the optimal parameters of the vibration absorber, namely the optimal frequency ratio, the optimal damping ratio and the optimal mass ratio, so that the structure in different Frequency excitation get the best damping effect. In this paper, the multi-objective optimization technology based on evolutionary algorithm is combined with the multi-attribute decision-making method. In view of damping system with damping in main system, the optimization and decision-making of dynamic vibration absorber are studied. For multi-objective optimization problems, an improved non-dominated solution-ordering multi-objective evolutionary algorithm (NSGAII) is used to find the Pareto optimal solutions. The Pareto optimal solutions form the decision matrix, and objective weighted entropy method Then we use the TOPSIS (Multi-Attribute Decision Making) algorithm to study the MADM and rank the Pareto optimal solutions. In this paper, an example of optimal design of dynamic vibration absorber with four design parameters and three objective functions is given.